Non-Standard Finance plc Capital Markets Day. 29 November 2017

Transcription

1 Non-Standard Finance plc Capital Markets Day 29 November 2017

2 2 NON-STANDARD FINANCE CAPITAL MARKETS DAY 29 NOVEMBER 2017 John van Kuffeler Founder and Group Chief Executive

3 3 NON-STANDARD FINANCE CAPITAL MARKETS DAY 29 NOVEMBER 2017 Agenda NSF Group and market overview John van Kuffeler, Group Chief Executive, NSF plc Branch-based lending Miles Cresswell-Turner, CEO Everyday Loans Guarantor loans Marc Howells, MD Guarantor Loans Division Break Home credit Loans at Home David Thompson, CEO Loans at Home Jono Gillespie, CFO Loans at Home IFRS9 and funding Nick Teunon, CFO NSF plc Summary John van Kuffeler Close

4 4 The vision, as set out in 2015 To be a leading participant in the UK s non-standard finance sector A sector with strong growth prospects, serving 10 million adults

5 5 NON-STANDARD FINANCE CAPITAL MARKETS DAY The vision, as set out in NOVEMBER 2017 Why are we different? When lending direct, we meet our customers face-to-face

6 6 NON-STANDARD FINANCE CAPITAL MARKETS DAY 29 NOVEMBER 2017 Progress so far NSF is one of the UK s leading providers of non-standard unsecured credit Key stats Listed Market cap Staff Net loan book 238m > m Locations Customers Locations Agents Net debt 1 >158, >1, m Overview Three acquisitions made in August 2015, April 2016 and August 2017: branch-based unsecured lending: Everyday Loans guarantor loans: George Banco and TrustTwo home-collected credit: Loans at Home Long-term funding in place Blue-chip shareholder base ¹ Net debt as at 31 October 2017 calculated as balance sheet debt ( 186.5m) minus balance sheet cash ( 10.0m)

7 Product overview Business performance 7 NON-STANDARD FINANCE CAPITAL MARKETS DAY 29 NOVEMBER 2017 Our three business divisions Branch-based lending Guarantor loans Home credit Market position #1 #2 #3 Acquisition Date: April 2016 April 2016/August 2017 August 2015 Net Loan Book 1 ( m): Annual loan book growth 1 20% 33% 40% Number of staff Number of customers 1 45,200 16,200 96,800 Loan Size ( m): 1k - 15k 1k 10k 100-1k Duration: 1 5 years 1 5 years weeks APR Range: 24% 299% 37% - 62% 164% - 733% Average Customer Income: c. 30,000 c. 24,800 c. 14,500 1 As at 31 October Note loan book growth figure for guarantor loans is on a pro forma basis

8 8 Macroeconomic backdrop

9 9 NON-STANDARD FINANCE CAPITAL MARKETS DAY 29 NOVEMBER 2017 Employment Employment is at all time highs Unemployment lowest since Employment rate % Latest ONS data: o Headline employment rate: 75.0% o Unemployment rate: 4.3% Jul to Sep 2012 Jul to Sep 2013 Jul to Sep 2014 Jul to Sep 2015 Jul to Sep 2016 Jul to Sep UK unemployment rate % al people that are active Jul to Sep 2012 Jul to Sep 2013 Jul to Sep 2014 Jul to Sep 2015 Jul to Sep 2016 Jul to Sep 2017

10 10 NON-STANDARD FINANCE CAPITAL MARKETS DAY 29 NOVEMBER 2017 Earnings Adults on low pay has dropped from 20.5% of the population in 2015 to 18.4% in Since 2013 the income of the lowest 10% of earners has increased by 16.2% - twice the rate of the top 10% Annual growth in gross earnings p Lowest 10% 2.6% 1.0% 3.7% 8.4% 2.2% Note 2017 figures are provisional 1 low pay is defined as the value that is two-thirds of median hourly earnings and high pay is defined as the value that is 1.5 times median hourly earnings. Source Annual Survey of Hours and Earnings (ASHE) Office of National Statistics

11 11 NON-STANDARD FINANCE CAPITAL MARKETS DAY 29 NOVEMBER 2017 Inflation CPI inflation projection 1 Inflation has been increasing 3% in September 2017 Transport, and food and non-alcoholic drink prices have been important factors in driving the changes in the rate Food inflation is at its highest for four years, driven by the drop in Sterling following the EU referendum But, inflation is expected to peak at 3.2% in October before falling back Source Inflation report, November Bank of England 1 based on constant nominal interest rates at 0.5%, other policy measures as announced

12 12 NON-STANDARD FINANCE CAPITAL MARKETS DAY 29 NOVEMBER 2017 Income versus inflation Tenth percentile of earners have seen incomes rise strongly in recent years up over 16% since 2013 Inflation over the same period is up c6% These consumers are therefore well-placed to cope with current level of inflation No signs of increased financial stress in any of our business divisions All three divisions are experiencing reduced levels of impairment

13 13 NON-STANDARD FINANCE CAPITAL MARKETS DAY 29 NOVEMBER 2017 Brexit threat or opportunity? We are a UK-focused business We are not unduly exposed to the international migrant community There has been no impact on our business to-date Uncertainty not good for business or the economy We already have long-term funding in place

14 14 NON-STANDARD FINANCE CAPITAL MARKETS DAY 29 NOVEMBER 2017 Key drivers of demand Low paid Low credit status Low paid Low credit status Credit impaired Credit impaired Self-employed Recently arrived immigrants Risk appetite of mainstream lenders c.1% of total work force at or below minimum wage² c.15% of total work force self-employed³ Over 912,000 consumer County Court Judgements 4 2.9m Recently arrived migrants 5 1 LEK consulting Executive Insights April ONS: Low Pay in the UK: April ONS: UK Labour market, May Registry Trust Limited Press release, 1 February Migrants to the UK from Sept 2012 to Sept 2016 ONS: Overview of the UK population, February 2017

15 15 NON-STANDARD FINANCE CAPITAL MARKETS DAY 29 NOVEMBER 2017 Low pay changes to the national minimum wage and national living wage Those on low incomes have benefited from a 4.4% CAGR in the National living wage since 2013 This rate of growth is expected to continue to 2020 Year 25 and 21 to and 18 to 20 Under Apprentice over over Oct16 to Mar Apr16 to Sept National minimum wage 25 and over National living wage OBR Forecasts Source Office of Budget Responsibility

16 16 NON-STANDARD FINANCE CAPITAL MARKETS DAY 29 NOVEMBER 2017 Credit impaired Mainstream banks tightening scorecards Increase in County Court Judgments in England and Wales Increased use of bailiffs by councils and others: Change in CCJs YoY vs 2016 Q % Q % Q % In councils passed 2.1m debts to bailiffs In this had increased to 2.3m Source: Stop The Knock - Money Advice Trust, November 2017

17 17 NON-STANDARD FINANCE CAPITAL MARKETS DAY 29 NOVEMBER 2017 Self-employed 15.5% Total number of self-employed % of total workforce that is self-employed 4, % 4, % 4, % 4, % 4, % 3, % 3, % Jan-Mar 2009 Jul-Sep 2010 Jan-Mar 2012 Jul-Sep 2013 Jan-Mar 2015 Jul-Sep ,500

18 Dec-12 Mar-13 Jun-13 Sep-13 Dec-13 Mar-14 Jun-14 Sep-14 Dec-14 Mar-15 Jun-15 Sep-15 Dec-15 Mar-16 Jun-16 Sep-16 Dec-16 Mar-17 Thousands 18 NON-STANDARD FINANCE CAPITAL MARKETS DAY 29 NOVEMBER 2017 Immigration The number of immigrants coming to the UK continues to rise Net long-term international migration was estimated to be +246,000 in year ending (YE) March 2017, down 81,000 from +327,000 in YE March 2016 There has been a net increase every year Immigrants are a small proportion of our customer base Net migration Gross immigration 100 0

19 19 NON-STANDARD FINANCE 2016 FULL YEAR RESULTS APRIL 2017 Regulatory backdrop

20 Non-executive Executive 20 NON-STANDARD FINANCE CAPITAL MARKETS DAY 29 NOVEMBER 2017 Our highly experienced Board is in tune with the regulatory environment John van Kuffeler Group CEO Nick Teunon Group CFO Miles Cresswell-Turner Executive Director Charles Gregson Non-Executive Chairman Niall Booker Non-Executive Director Heather McGregor Non-Executive Director

21 21 NON-STANDARD FINANCE CAPITAL MARKETS DAY 29 NOVEMBER 2017 What we have achieved so far Established a good relationship with FCA April 2016 change of control for Everyday Loans June 2016 FCA licence for Everyday Loans and TrustTwo May 2017 FCA licence for Loans at Home September 2017 FCA licence for George Banco Engaged with other key stakeholders MPs/ members of House of Lords Consumer groups (StepChange, CAB, Money Advice Trust) Think Tanks Appointed to National Executive of Consumer Credit Association

22 22 NON-STANDARD FINANCE CAPITAL MARKETS DAY 29 NOVEMBER 2017 Key regulatory themes for NSF No material issues for branch-based lending or guarantor loans We are addressing some specific questions around home credit: Why models of predictable financial stress in other sectors do not apply FCA examining refinancing but repeat borrowing in home credit is not the same as rollovers in payday or other running account products Why APRs are so high? o Loan amounts are small and for short periods o High loss rates and an expensive operating model o Actual APRs are lower as most customers pay late Why other models are unable to service this large customer segment Waterbedding o CCJs/other debt default/unpaid bills/bailiff activity o Illegal money lending

23 23 NON-STANDARD FINANCE CAPITAL MARKETS DAY 29 NOVEMBER 2017 Current initiatives Continuing our outreach programme in Westminster Responding to consultations: FCA High Cost Credit Review HM Treasury breathing space Treasury Select Committee household debt Matthew Taylor Review and Select Committee proposals Horizon scanning Embedding Vision, Mission and values/behaviours Planning for Senior Managers and Certification Regime

24 24 NON-STANDARD FINANCE 2016 FULL YEAR RESULTS APRIL 2017 Competitive landscape

25 bn 25 NON-STANDARD FINANCE CAPITAL MARKETS DAY 29 NOVEMBER 2017 The supply of alternative lending has increased since Source: NSF estimates Inactive unsecured Online unsecured lenders Logbook loans Branch-based lenders Pawnbroking Guarantor loans HCSTC Online lenders Home collected credit Car finance Rent to buy Credit Unions Store cards Mail order Point of sale loan Sub-prime Credit Cards 2016 ( bn) CAGR (34%) 0.2 n/a % % 0.2 (5%) % 0.2 (13%) 0.8 (4%) % 0.5 (2%) 1.3 7% 1.6 (1%) 2.0 1% % %

26 26 NON-STANDARD FINANCE CAPITAL MARKETS DAY Competitive landscape Loan Size 29 NOVEMBER HCSTC price cap 1000 (Lift) % 50% 75% 100% 200% 1000% APR

27 27 NON-STANDARD FINANCE CAPITAL MARKETS DAY 29 NOVEMBER 2017 Summary of our marketplace Branch-based lending: Macro economic backdrop has been positive with record levels of employment No material issues from a regulatory perspective Few profitable competitors Guarantor loans: Macro economic backdrop has been positive with record levels of employment No material issues from a regulatory perspective Opportunity to strengthen our #2 position further as a number of smaller players continue to make losses Home credit: Macro economic backdrop has been helped by above average earnings growth for low paid FCA examining refinancing Market opportunity: we have effectively acquired a business more than half our size, for 5m investment 437 agents added 40% loan book growth before peak lending season 20 new offices 90 additional staff

28 28 NON-STANDARD FINANCE CAPITAL MARKETS DAY 29 NOVEMBER 2017 Conclusions on our marketplace Loan Book Growth Impairment: revenue Risk-adjusted margin Target 12m to Oct-17 12m to Jun-17 12m to Oct-17 12m to Jun-17 12m to Oct-17 20% 20% 19.6% 17.9% 35.7% 37.30% 20% 33% 15.3% 14.6% 27.5% 30.50% 20% 40% 37.5% 32.9% 95.4% 98.20%

29 29 NON-STANDARD FINANCE CAPITAL MARKETS DAY 29 NOVEMBER 2017 Questions

30 Branch-based lending Miles Cresswell-Turner CEO everydayloans for everydayliving

31 Agenda 1. Introduction 2. History 3. Everyday Loans business model 4. Customer demographic 5. Customer waterfall 6. Strategy for growth 7. Summary everydayloans for everydayliving Page 31

32 1. Introduction - overview Everyday Loans is the UK s largest branch-based lender of unsecured loans to sub-prime borrowers It has a network of 53 national branches - 5 branches opened in branches opened in 2017 By using a face-to-face model, our USP is being able to lend profitably to those customers that others can t or won t Our loans are unsecured and distributed through three main channels: - Brokers 33% - Direct to brand 36% - Own book renewals and former borrowers 31% Page 32 everydayloans for everydayliving

33 2. History - timeline Founded in 2006 Financial crisis Large numbers of consumer finance businesses exited the market including: o Black Horse o Citifinancial o HFC/Beneficial o Welcome o London & Scottish Everyday Loans was the only remaining branch based consumer lender (not high cost, short-term) in the UK June 2012 Purchased by Secure Trust Bank December 2015 Purchase by NSF Announced April 2016 Acquisition Completed following FCA change of control June 2016 Full FCA Licence granted August 2017 George Banco acquired No. of branches Receivables ( m) ^ ^ as at October 2017 everydayloans for everydayliving Page 33

34 2. History - timeline everydayloans for everydayliving Page 34

35 2. History timeline - Impairments as a % of average net receivables 20% 18% 16% 16% 15% 10% 10% 10% 8% 8% 8% 7% 9% 8% 5% 0% YTD Annualised to 31 October 2017 Delinquency continues to receive management focus as we strive to optimise growth. Collection policies and procedures are being continually revised and updated to take into account lessons learned. The business extended its customer profile further down the credit spectrum in 2016 and while impairment increased slightly, it is within tolerance and risk adjusted margins remain strong. Page 35 everydayloans for everydayliving

36 3. Everyday Loans business model Branches offer full service lending and collecting Off-high street retail premises and first floor offices National coverage - majority of customers live within five miles or 30 minutes of a branch Customers are able to establish/repair credit history and branches provide money management service for financially unsophisticated customers All loans are unsecured with homeowners making up approximately 20%-25% of customers Risk based pricing allows true full-spectrum lending for the right loan amount at the correct price Customers are focused on certainty of obtaining credit and monthly payment, not rate: 1,000 to 15,000 24% APR to 299% APR 12 months to 60 months everydayloans for everydayliving Page 36

37 4. Customer demographic Average loan size is 3-4,000 58% of loans being 4,000 or less Over 57% are under the age of 40 45% are single 71% earn more than 1,500 per month 42% earn more than 2,000 per month 32% of loans are at an interest rate of less than 50% 66% have no dependents 42% rent; 28% are homeowners; 23% live with parents 71% have been at the same address for more than three years 75% have been at their job for more than three years everydayloans for everydayliving Page 37

38 5. Customer waterfall as at 30 June 2017 everydayloans for everydayliving Page 38

39 5. Customer waterfall update to 31 October % UK RESIDENTS, EARNING AVERAGE INCOMES, CREDIT IMPAIRED, THIN CREDIT FINANCIAL BROKERS 72% of applications (33% of loans booked) DIRECT 25% of applications (36% of loans booked) OWN BOOK RENEWALS/FORMER BORROWERS 3% of applications (31% of loans booked) Central 65% declined Duplicates /incorrect info Credit history Customer waterfall Credit score 35% accepted 22% receive telephone interview In-branch 6% attend branch and 3% get a loan 13% no response/decline 16% declined/fail I&E everydayloans for everydayliving Page 39

40 6. Strategy for growth Annual trends positive but we felt that we could do more and needed a change of pace and ambition everydayloans for everydayliving Page 40

41 6. Strategy for growth - step 1: Strengthened and reinvigorated management team Miles Cresswell-Turner CEO Jon Wiggins MD Branch Network Jason Bovington Credit Risk Andrew Wayland Marketing Steven White CFO Jonathan Hole Compliance Mareena Flint Head of HR & Training Miles Cresswell-Turner: 33 years experience in Financial Services industry, 18 years in PE Executive Director and co-founder of Non-Standard Finance Joined Everyday Loans as Chairman in April 2016; became Exec Chairman in May 2017 Became CEO of Everyday Loans in September 2017 Jon Wiggins: 28 years experience in Financial Services Industry Joined Everyday Loans in May 2017 Previously at CitiFinancial and Citibank Jason Bovington: Helped set up Everyday Loans as Head of Risk in years Financial Services experience Previously Head of Risk HFC Bank PLC Andrew Wayland: Helped set up Everyday Loans as Head of Marketing in 2006 Business owner Columbell Communications for 5 years Previously Head of Commercial Development Tech start-up Steven White: 28 years experience in Financial Services industry Arthur Andersen, UBS & Deutsche Bank Previously at Link Financial UK Chartered Accountant ICAEW Jonathan Hole: 33 years experience in Financial Services industry Joined Everyday Loans in August 2017 Previously worked for Barclays, Santander and Aldermore Mareena Flint 25 years experience within HR & Training Joined Everyday Loans in January 2017 Previously Provident Financial Group Chartered member of the CIPD everydayloans for everydayliving Page 41

42 6. Strategy for growth - step 2: Invested in our network and supporting infrastructure 1. Expanding the branch network and new premises 12 new branches relocated/refurbished 16 branches (8 still in progress) Additional office space in Bourne End 2. Improved service to customers Moved to same day Faster Payments Introduced esignature Launched 12-month loan product 3. Hired additional key personnel: New Chief Accountant and increased analytics resource Dedicated In-House Trainer and additional training instructor Head of Collections Head of IT 4. Established bespoke training capabilities Sales, Collections and Management Development 5. Improved employee communications Launched Employee Forum Launched videoconference in all branches Started a regular staff newsletter Grapevine Launched intranet Page 42 everydayloans for everydayliving

43 6. Strategy for growth - step 3: increasing productivity 1. Sharing of best practice Identified best in class managers Began a process to cross-fertilise this to other branches Work begins on the Everyday Way 2. Increasing number of leads Building deeper partnerships with key brokers SEO and digital marketing 3. Increased operational efficiency Dialler to allow outbound call campaigns and resource sharing across branches Launched new Areas to allow pooling of resources and extended opening hours 4. Upskilling of existing staff and management Roll-out of training modules on Sales, Collections and Management Development 4. Product expansion Launch of Selfy product Launch 12-month product Page 43 everydayloans for everydayliving

44 Thousands 6. Strategy for growth - the results: application volumes Change of gear Jan-17 Feb-17 Mar-17 Apr-17 May-17 Jun-17 Jul-17 Aug-17 Sep-17 Oct-17 everydayloans for everydayliving Page 44

45 Thousands 6. Strategy for growth - the results: new borrower applications to branches Jan-17 Feb-17 Mar-17 Apr-17 May-17 Jun-17 Jul-17 Aug-17 Sep-17 Oct-17 everydayloans for everydayliving Page 45

46 6. Strategy for growth - the results: new borrower conversion rates 9.0% 8.5% 8.0% 7.5% 7.0% 6.5% 6.0% 5.5% Jan-17 Feb-17 Mar-17 Apr-17 May-17 Jun-17 Jul-17 Aug-17 Sep-17 Oct-17 everydayloans for everydayliving Page 46

47 6. Strategy for growth - the results: new borrower loan units written 2,600 2,400 2,200 2,000 1,800 1,600 1,400 1,200 1,000 Jan-17 Feb-17 Mar-17 Apr-17 May-17 Jun-17 Jul-17 Aug-17 Sep-17 Oct-17 everydayloans for everydayliving Page 47

48 6. Strategy for growth - the results: yield on new loans written 63% 62% 61% 60% 59% 58% 57% Jan-17 Feb-17 Mar-17 Apr-17 May-17 Jun-17 Jul-17 Aug-17 Sep-17 Oct-17 everydayloans for everydayliving Page 48

49 6. Strategy for growth the results: lower total delinquency (% of average net receivables) 9.5% 9.0% 8.5% 8.0% 7.5% 7.0% Jan-17 Feb-17 Mar-17 Apr-17 May-17 Jun-17 Jul-17 Aug-17 Sep-17 Oct-17 everydayloans for everydayliving Page 49

50 6. Strategy for growth further expand our branch network 12 locations identified and in progress; 9 branch managers identified and in-training All planning to launch in H1 18 Streamlined opening process, enhanced staff selection methodology, new 2 week induction plan 3-6 branches per year thereafter Targeting branches by end of 2020 Reminder of branch economics Pre-opening P&L costs up to 75k 0-12 months EBIT (105)k months EBIT 165k months EBIT 300k everydayloans for everydayliving Page 50

51 6. Strategy for growth - further improve our productivity More leads from new corporate relationships with lead generators and corporate affiliations Increase our conversion rate Will again remove the lowest converting brokers Recognise our market position by asking more of brokers Fully embed best practice across the network Branch manager conference Leaders conference Roll out of Area Manager methodology New courses from our Training and Collections functions Efficient communications via the website and VC tools Very proactive education, methodology and partnerships to continue our focus on collections Page 51 everydayloans for everydayliving

52 6. Strategy for growth - Enhanced performance required significant investment Our fixed cost base has increased as a result This is a single step increase, annualising over two years and includes: A further 12 new branches in H Additional staff for existing branches Relocation and upgrade of existing branches Additional space at Bourne End for Network and Guaranteed expansion Upskilled Senior Management Installation and utilisation of network telecoms dialler Enhanced Training, Compliance, Credit, IT and Finance Total admin costs increase by 1m in FY 2017 and 3m in FY 2018 The opening of the Group s 50 th branch in Bradford earlier this year everydayloans for everydayliving Page 52

53 7. Summary The opportunity for growth remains significant with unsatisfied demand and few direct competitors Whilst an expensive service to deliver, our branch-based model is proven in delivering profitable growth We have made significant investment in our infrastructure : New / relocated branches People Training Products Culture This investment is already yielding positive results: Loan book growth +20% Delinquency down Increased risk-adjusted margins Plan for 2018: 12 more branches to open Further productivity gains There is a great sense of excitement about the prospects for our business Page 53 everydayloans for everydayliving

54 Questions everydayloans for everydayliving

55 NSF Guarantor Loans Division One Division, One Team, Two Brands, Two Locations everydayloans for everydayliving Page 55

56 1. Introduction George Banco/TrustTwo (Guarantor Loans Division) is the clear #2 in guarantor loans 82 employees Beckington, Somerset (58) and Bourne End, Berkshire (24) 1 16,200 Customers (and Guarantors) m loan book (before fair value adjustments) 1 Key areas of focus: i. Execute and complete 100-Day Plan ii. Ensure full recovery at George Banco from lending hiatus earlier in 2017 (Sept - Nov 2017) iii. Stabilise both businesses and build momentum across both locations (Oct-Dec 2017): Strategy now based on: One Division One Team Two Brands Two Locations Defined and agreed pathway to Target Operating Model (TOM) Build Business Architecture; People-Process-Technology Execute short-term tactics to maintain capture of market share Crystallise strategy based on data analytics 1 As at 31 October 2017 everydayloans for everydayliving Page 56

57 2. Management Marc Howells Managing Director Highly experienced leadership team covering two operations and locations Neil Critchley Chief Operations Officer James Broderick Head of Development Shared Central Services provided by Everyday Loans Local oversight of shared central services Shared Services Beckington Bourne End Additional hires in Q1 2018: Operations manager Bourne End Additional front-end developers Jess Franklin Head of Sales Jen Bradbury Team Manager Sales Alex Przytocki Head of Collections Liisa Sabah Team Manager Support Dave Beer Head of Underwriting Lakveer Raj Team Manager Collections everydayloans for everydayliving Page 57

58 2. Market opportunity Guarantor loans outstanding across the industry ( m) 1 Provider Loan book ( m) Total receivables of c. 440m at the end of 2016 (FCA) Amigo dominates with 80%+ share Current GLD market share is c.8-10% Annual issuance of c. 380m Historic CAGR of c30% per annum Extrapolation of recent trends implies potential receivables of up to 1bn by year end Based on latest public filings everydayloans for everydayliving Page 58

59 million 3. Headline objectives Capitalise on strong underlying market demand Strengthen our position as the clear #2 Share best practice Optimise key performance metrics at each point of the customer journey Focus on combined market share - relaxed as to growth split between brands Targets: double loan origination by the end of year-end receivables of > 80m c.20% return on asset by end of 2019 Targeted loan book growth for Guarantor Loans Division Acquisition by NSF This ambitious target will be achieved through the transition to our Target Operating Model TT net loan book GB net loan book Combined everydayloans for everydayliving Page 59

60 4. Our Target Operating Model Focus will be on four acquisition channels across two brands Both brands have clear strengths but in different channels: Financial brokers George Banco Price comparison websites TrustTwo Direct TrustTwo Branch-referrals TrustTwo Single operating system: Move to a single platform in 2018 New management information portal based on GB tech Targeting launch within 12 months Attract and retain the best talent Common underwriting approach and dashboard Two collections teams (0-90 days and >90 days) Launch of Customer Stratification Financial brokers Consumer demand PCWs Direct Common underwriting and dashboard Single loan management system Collections for up to 90 days Centralised collections > 90 days Centralised risk management Branch referrals everydayloans for everydayliving Page 60

61 4.1 Leveraging our two brands Both brands already have clearly identified and different market positions TrustTwo known as a significant and competitive guarantor loan product on comparison websites George Banco is known to brokers as a core provider of guarantor loans with a good conversion rate Continuing to operate both brands will maximise market coverage and provide multiple capture points Customer segments vary by source, quality, profile, price - a guarantor loan IS NOT a simple product Current data deficit on interaction between both brands need detailed analysis on: Side-by-side comparisons; in direct competition Hierarchical; GB processes TT declines Blend of above Marketing spend to be focused at TrustTwo while George Banco will remain broker-driven. Page 61 everydayloans for everydayliving

62 4.2 Two brands, one operating system A single platform leveraging the market positioning of both brands: Take the best of both New infrastructure for the Guaranteed Loans Division Basic back office with ELL front-end build Ryland PanCredit + SuperUser Nostrum NSF GLD SuperUser 2 TBA ELL own front-end IP Reduce reliance on 3rd party dependencies Enable a straight-through-processing ( STP ) approach for standard applicant allowing time to be spent on applications where personalised analysis would benefit the process significant efficiencies and economies of scale to be realised One system Multiple (4) journeys everydayloans for everydayliving Page 62

63 4.3 Attract and retain the best talent Define Operational Architecture including a clear strategy for two operational locations (Jan 2018) Develop shared Vision, Mission, Values Clearly defined management structure (Local & Central) Harmonised incentive programs (Meritocracy) Succession planning introduced Senior CAM role Stronger requirements on recruitment Fit-for-purpose Robust Training program Cradle-to-grave Introduced 5-day induction program for new employees Management Training; Sales Process Underwriting Collections Performance Management Time Management Develop GLD Academy Management incentive on people turnover ( regretted ) everydayloans for everydayliving Page 63

64 4.4 Acquisition channels 26% Current GB loan mix 6% 68% Broker Top-ups Organic 5% 9% 36% 10% Current TT loan mix 15% 16% 9% Broker Top-ups Organic Price comparison ELL online decline ELL Branch decline Lead generator Current combined loan mix 2% 2% 3% 10% 7% 53% 23% Broker Top-ups Organic Price comparison ELL online decline ELL Branch decline Lead generator Aspirational channel mix development: to improve balance further with growth in all channels Leverage exiting Group leads and existing customers to optimise acquisition costs Seek to diversify from overweight broker position Spread risk of margin compression from price comparison websites Page 64 everydayloans for everydayliving

65 4.5 Customer Stratification Map customer profiles journeys across both brands 120,000 GB leads + 82,000 TT leads Modify customer journey for both brands: Common entry point enables profiling, passporting and bespoke communication to each lead value creation Re-define de-duplication process across Division / Group Live-tracking of leads across operational areas Live waterfall; trigger points mapped to customer journey Develop levers to impact trigger points New communications test platform: Test-Learn-Invest Implement basic communications tool SMS, , What sapp Credit quotation search against filtered, accepted leads Two-way SMS communication Live chat Financial brokers Consumer demand PCWs Direct Common underwriting and dashboard Single loan management system Collections for up to 90 days Centralised collections > 90 days Centralised risk management everydayloans for everydayliving Branch referrals Customer profiles mapped, live tracking, duplicates removed and leads distributed Page 65

66 Applicant - Gauge 4.6 Underwriting Illustrative George Banco Pricing Model Develop common underwriting platform Two teams of highly trained underwriters (ACEJPSIII) Proven cycle of development for underwriters: (i) Customer Services (ii) Collections (iii) Underwriting (iv) First- Instalment-Defaulters Incentives linked to balanced scorecard, good customer outcomes/customer service, volume and delinquency Automated data capture and scoring Risk-based pricing 2019 target: 20% straight-through-processing, 80% subjective Page 66 Decision Score G or less Score H or less Score I or less Score J or less Score K or less Score L or less Total Score A or less Score B or less Guaranator - Gauge Score C or less Score D or less Score E or less Decline Decline Decline Decline Decline Decline Decline 61.8% 61.8% 61.8% 61.8% 61.8% Decline 61.8% 61.8% 61.8% 49.7% 49.7% Decline 61.8% 49.7% 49.7% 49.7% 49.7% 61.8% 49.7% 49.7% 49.7% 49.7% 49.7% 61.8% 49.7% 49.7% 49.7% 49.7% 49.7% Score F or less Total Trust Two Pricing Model TrustTwo Pricing APR Price comparison websites 37.90% Price comparison websites > 4, % Standard - Guarantor homeowner 43.80% Standard - Guarantor non-homeowner 48.90% everydayloans for everydayliving

67 4.6 Risk management Harmonised Lending Manuals (December 2017) Move to common Credit Reference Agency (CRA) CallCredit Automate use of CallCredit products CallCredit to develop bespoke Guarantor Loan Scorecard Automated initial assessment of affordability (Share/TAC/ONS) Collection tools for underwriting (Retreiver, Lexus Nexis) Use of social media and web data (Facebook, LinkedIn, Google Maps) Use of available face-to-face communications (F2F), FaceTime / Skype Post-2019 use of machine learning and facial recognition everydayloans for everydayliving Page 67

68 4.7 Collections Harmonised Collection Manuals (December 2017) Merge People-Process-communications Implement GB processes with TT (Work queues, rewrites) Front-end collections up to 90 CD Centralise during 2018 (when able); Collections > 90CD Fraud IVA / Bankruptcies DMA Implement First Instalment Defaulters in KPIs everydayloans for everydayliving Page 68

69 4.7 Data management and reporting Combine both businesses onto a single management platform in 2018 Common collection of data & metrics Common data warehousing Customer and process waterfalls Automated production of KPIs Forecasting based on latest trends Leveraging of database to analyse performance by cohort everydayloans for everydayliving Page 69

70 5. Conclusion Strong position in a rapidly growing market Highly experienced management team with proven track record of delivering profitable growth Long-term funding in place Complementary positioning of two leading brands 100-day plan complete, now moving towards Target Operating Model: Single loan management platform and data analytics Customer stratification with single entry point across multiple brands Common underwriting and risk management processes Localised collections, supported by central collections team (>90 days) Real-time management information Tailored communications tools A/B testing of new products and channels Recent trading performance encouraging Page 70 everydayloans for everydayliving

71 Questions everydayloans for everydayliving Page 71

72 72 NON-STANDARD FINANCE CAPITAL MARKETS DAY 29 NOVEMBER 2017 Coffee break

73 1 29 November 2017

74 Agenda Market overview Loans at Home overview Key success factors The market opportunity Operational results vs 2016 Expansion-related costs New technology Outlook and Summary

75 Market overview Stable market of around 3 million regular users of which c1.8m historically borrow at any one time. Recent sharp decline in Provident customer numbers caused c1.8m to fall to c1.6m 1 Customer incomes approximately 10k to 15k in C2, D and E socio-economic groups Typical loan size 200 to 1,000 Weekly collections from the customer's home. Regulated by the FCA 1 Technical Annex 1 High Cost Credit Review - FCA

76 Loans at Home - history Established in 1938, Loans at Home has nearly 80 years of experience in the Home Collected Credit market Formed from Home Collected Credit businesses of S&U PLC and acquired by NSF plc in August 2015 Since acquisition, the business has received significant investment: Management Training Technology Compliance infrastructure Office network No change to core agent / customer relationship-focused model Page 76

77 Loans at Home business model Focused exclusively on Home Collected Credit No default fees or default interest charged on any loans Service delivered exclusively by self-employed agents visiting customers homes, supported by a UK-wide network of offices Offer a simple range of four products based on term of loan: Weeks Charges per 100 Total Payable Weekly Rate APR % % % % Page 77

78 Loans at Home size Just under 100k customers in October 2017 Service delivered by a team of over 1,000 self-employed agents 20 new locations added to branch network in 2017 to support strong growth. Currently 65 branches. c350 employees supporting the agents Page 78

79 Loans at Home - customer profile c40% aged c25% aged c70% female c50% have employed person in household c92% C2, D or E c90% rent 65% council, 25% private c72% receive benefits excl. child benefit Average annual household income 16,000 c96% have a mobile phone c89% have online access c93% have a bank account c35% have a PayPal account c5% use pre-paid debit cards c24% overdraft facility c15% have direct debit loan c18% have goods on credit Page 79

80 Loans at Home - customer profile Use of loan c27% home improvement c13% presents c18% holidays c9% bills c8% car expenses c5% baby/child expenses c20% other Page 80

81 Loans at Home - customer satisfaction Source: Customer research undertaken by PCP Market Research among 300 customers Other NPS scores taken from npsbenchmarks.com UK consumer net promoter benchmark Page 81

82 Key success factors Strong Agent/Customer relationship Page 82

83 Key success factors agent/customer relationship Recently captured some customer stories showing the unique relationship with their Loans at Home agent Like to share a few of those stories. Page 83

84 Key success factors Strong Agent/Customer relationship Open, positive culture Page 84

85 Key success factors - our culture Culture is an ongoing key strategic focus Held workshops in early 2017 with stakeholders from all levels and areas of the business Established what really mattered to people The Key cultural elements that we strive to protect and improve are: Team-minded doing what s right for the team over yourself Integrity vital at all levels of the business Customer service setting the highest possible standard Keep it simple vital for our industry Page 85

86 Key success factors - our culture Staff and agents are treated with dignity and respect We are a company that listens to our people Senior team regularly visit branches and spend time with staff and agents Feedback sought and acted upon Significant competitive advantage in current market Future growth dependent on retaining the excellent team we currently have and being able to continue to attract the best people in the industry Our open, positive culture allows us to do this. Major success in 2017 and opportunities still presenting themselves. Page 86

87 Key success factors - our culture Culture formed the foundation of our business Technology platform also vital Established Pillars of our business. Regularly reviewed, to ensure we re following the right path. Together, the foundation and pillars form Our Home Page 87

88 Page 88 Key success factors - our culture

89 Key success factors Strong Agent/Customer relationship Open, positive culture Sector leading technology (see later slides) Experienced management team great blend of knowledge and experience Page 89

90 Key success factors experienced management David Thompson Chief Executive Officer Paul Gill Chief Risk Officer Jono Gillespie CFO Christine Rangeley HR Director Mike Palmer Chief Operating Officer Sam Beardsley Head of Operational Risk Simon Brown Head of Compliance Chris Pearson Head of FPA Jamie Place Head of IT Sarah Day Company Secretary Lisa Quirke Head of Development Kat Hackett Head of Marketing Gordon Withers Head of Operations support Divisional Managers x3 Asif Nadeem Head of BI and Architecture Clayre Hughes Head of Business Change 10 Regional Managers 46 Area Managers c160 Business Managers c.1,000 Agents Page 90

91 Key success factors Strong Agent/Customer relationship Open, positive culture Sector leading technology (see later slides) Experienced management team great blend of knowledge and experience Key focus on looking after current agents, only adding quality new agents Supporting agent and customer growth with investment in infrastructure: Training Compliance and oversight Field Managers in appropriate locations New offices Close monitoring of performance via tailored MI Funding Page 91

92 Millions of customers million The market opportunity Provident Decline Provident s move away from selfemployed to employed model significantly disrupted the market Problems with the new model led to sharp decrease in Provident's customer numbers and receivables Provident s ex-customers still have lending needs Customers (m) Receivables ( m) - RH scale 1, Not what we planned for, but major opportunity to increase market share Oct-17 0 Page 92

93 The market opportunity Recognised need for carefully managed approach to growth given missed-step in Summer 2016 As previously shared, major reason for sub-optimal growth outcomes in 2016 was due to growth via inexperienced agents Following Provident s strategy change, a large number of experienced agents with proven track records left Provident, but still wanted to be agents Loans at Home was less well-known to agents than others in the industry, but word quickly spread about our culture, leading many agents to believe we were the best partner for them Objective was to achieve original 2017 planned level of EBIT after temporary agent support payments but the opportunity was even greater than expected To harness the opportunity and underpin further future growth, we have invested a total of 5m in 2017 Page 93

94 The market opportunity Lessons learned from 2016 led to a better understanding of risks of growth. Risks managed by: Establishing P&L s for each agent Page 94

95 Page 95 The market opportunity example agent P&L

96 The market opportunity Lessons learned from 2016 led to a better understanding of risks of growth. Risks managed by: Establishing P&Ls for each agent Close monitoring of collections performance at agency level Strict approvals process for agent support packages Ensure supporting infrastructure grows ahead of customer growth Maintain tight focus on underlying business We are seeing the benefits of this process Page 96

97 Operational results vs ,050 Agencies 1, Jan-17 Feb-17 Mar-17 Apr-17 May-17 Jun-17 Jul-17 Aug-17 Sep-17 Oct-17 Nov-17 Dec-17 Total journeys Prior Year Page 97

98 Operational results vs 2016 Vacant Agencies Nov-16 Dec-16 Jan-17 Feb-17 Mar-17 Apr-17 May-17 Jun-17 Jul-17 Aug-17 Sep-17 Oct-17 12% 10% 8% 6% 4% 2% 0% Vacant Vacant % Page 98

99 Operational results vs 2016 New customers 7,000 6,000 5,000 4,000 3,000 2,000 1,000 - Jan-17 Feb-17 Mar-17 Apr-17 May-17 Jun-17 Jul-17 Aug-17 Sep-17 Oct-17 Nov-17 Dec-17 Actual Prior year Page 99

100 Operational results vs ,000 Total Customers 100,000 95,000 90,000 85,000 80,000 Jan-17 Feb-17 Mar-17 Apr-17 May-17 Jun-17 Jul-17 Aug-17 Sep-17 Oct-17 Nov-17 Dec-17 Page 100 Actual Prior Year

101 Operational results vs ,000 Quality Customers 60,000 55,000 50,000 45,000 40,000 35,000 30,000 Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Page 101

102 Significant network expansion To underpin the growth in agents and customers, 20 new branches were needed. These branches will also provide a platform for future growth Aberdeen Barnsley Basildon Berwick upon Tweed* Bromsgrove Chelmsley Wood Corby* Didcot Doncaster Dundee Gateshead Havant Kings Lynn* Leicester Milford Haven Newark Pontypool St Austell/ St Stevens* Wimbledon Wood Green (Enfield) * Opening soon Page 102

103 Financial results vs ,000 Quality Customers 60,000 55,000 50,000 45,000 40,000 35,000 30,000 Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Page 103

104 Financial results vs % Quality as % of Total Customers 1 60% 55% 50% 45% 40% Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Page Customers that have made 70% of their due payments over the previous 13-week period

105 Financial results vs 2016 Gross loan book arrears banding % mix 100% 90% 80% 70% 60% 50% 40% 30% 20% 10% 0% Jan-16 Apr-16 Jul-16 Oct-16 Jan-17 Apr-17 Jul-17 Oct-17 A B-C D-H I-L M Page 105

106 Financial results vs % Lending Product Mix % 90% 80% 70% 60% 50% 40% 30% 20% 10% 0% 24wk 33wk 42wk 45wk 50wk 75wk Other Page 106

107 Financial results vs Net Receivables m Jan-17 Feb-17 Mar-17 Apr-17 May-17 Jun-17 Jul-17 Aug-17 Sep-17 Oct-17 Nov-17 Dec-17 Actual Prior Year Page 107

108 Expansion-related costs Variety of costs incurred to support this one-off growth opportunity Temporary agent commission costs of c 3m in 2017 needed to support new agents until round developed. will significantly reduce in 2018 Additional infrastructure costs of c 2m in 2017 management/support staff, technology and new offices will increase to c 3.8m in 2018 as only part-year in 2017 New branches all heading towards profit generation in early 2018 Collectively, agents joining established branches are contribution positive in 2017 Page 108

109 New technology Why? At acquisition, technology in branches and head office but not mobile All agent : customer interaction involved pen and paper Slow, error prone process. Transaction details manually entered onto system weekly Slowed down MI and analysis Wanted the agent to hold and collect data at source Much faster and far less error prone Ensures regulatory compliance Removes need for manual data-input. Near real-time system updates. Significantly speeds up MI for agents and managers Better experience for agents and customers Page 109

110 New technology Phase 1 objectives Foundations Build a new platform for the new technology Stage 1 Collections app: All info needed for agent to collect and record outcomes Stage 2 Lending app Paperless loan origination process Stage 3 Balancing: Removes the need for data input and labour intensive weekly reconciliations Stage 4 Provide managers with mobile devices to increase time spent with customer Page 110

111 New technology Platform The new platform was vital for our technology journey. Partnered with boutique cloud data experts DataShed After a careful selection process, chose Microsoft Azure: Secure Take advantage of Microsoft s heavy investment in security Flexible Allows us to integrate all our existing and new technology Scalable Started small and added components as developed. Don t need to pay for peak power until needed Robust Cloud technology, multiple instances in multiple locations. Very pleased with performance and economics Page 111

112 New technology Apps Demo We d like to share more details with you about our apps They re available for you to play with at the back of the room Short video showing apps in action 6 weeks after rollout began, over 80% of all loans are processed through the lending app Page 112

113 New technology Phase 1 objectives review Stage 1 Collections All info will be entered directly into systems by agents via mobile apps Increased efficiency Instant access to customer data Reduce manual errors Remove paper collecting lists Stage 2 - Lending Ability to lend via mobile device Electronic agreements, request to call forms and affordability assessment forms Greatly enhanced agent and customer experience Processes built to ensure regulatory compliance Stage 3 - Balancing Centralisation of remaining administrative tasks into CRC Removal of unnecessary balancing and reconciliation tasks undertaken by agents and performance managers Stage 4 Mobile MI ipads for all Managers Full mobile access to all MI whilst outside of the office with agents or customers Secure and Robust Page 113 Foundation Cloud based platform for secure, scalable hosting of technology. All fully integrated with application process via web and Customer Relationship Centre (CRC)

114 New technology Phase 2 Phase 2 will be agent and customer-led Continue embedding and improving core apps, based on feedback from Agents customers Customer portal Gateway for customers to view account See balance and transactions Make a payment via card See what further lending options are available All to support, not replace, the agent/customer relationship Page 114

115 Outlook and Summary Strong progress already made: Significant expansion of network and business volumes loan book up 40% Much improved quality impairment falling Outlook for 2018: Full-year benefit from new agents hired in 2017 Support payments will reduce significantly as agencies become established Investment in infrastructure provides excellent platform for further growth Will continue to drive efficiency through technology Will seek to maintain cultural advantage Loans at Home is well-placed to deliver additional growth in 2018 Page 115

116 116 NON-STANDARD FINANCE CAPITAL MARKETS DAY 29 NOVEMBER 2017 Nick Teunon Chief Financial Officer

117 117 NON-STANDARD FINANCE CAPITAL MARKETS DAY 29 NOVEMBER 2017 Funding Refinanced our bank facilities in August 2017: 175m of six-year funding Additional 50m committed facility Provided by Alcentra, Beachpoint and Cairn All-in cost of 9% Plus 35m RCF from RBS (LIBOR+3.5%) Ample funding through to mid-2019 m

118 118 NON-STANDARD FINANCE CAPITAL MARKETS DAY 29 NOVEMBER 2017 IFRS 9 Effective 1 January 2018 with no restatement of FY17 results Moves from incurred loss to expected loss basis Impact most pronounced in NSF Home credit division: Seasonality drives substantial lending in November and December of each year with minimal incurred loss IFRS 9 will move impairment from Q1 of any year to Q4 of previous year minimal impact if loan book not growing but NSF Home credit growing fast No impact on lifetime profitability of any individual loan or cash flows from that loan No impact on debt covenants

119 119 NON-STANDARD FINANCE CAPITAL MARKETS DAY 29 NOVEMBER 2017 IFRS 9 estimated impact on 2016 closing balance sheet We have made good progress with IFRS 9 implementation and the methodology to be used. Based on this work we estimate that reported receivables at the end of 2016 would have been approximately 3%-7% lower under IFRS 9. As an illustration, the table below shows the impact of a 5% decrease in reported receivables together with the impact on the group's reported net assets at the same date after taking account of the deferred tax impact of the receivables adjustment. m 2016 as reported 2016 with 5% adjustment Changes Net loan book % Net assets %

120 120 NON-STANDARD FINANCE CAPITAL MARKETS DAY 29 NOVEMBER 2017 John van Kuffeler Founder and Group Chief Executive